Read full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=52713#.VKH8NcCAM4 Author(s) Xingchen Yu , Ernest Fokoué Affiliation(s) Center for Quality and Applied Statistics, Rochester Institute of Technology, Rochester, NY, USA . ABSTRACT The logistic normal distribution has recently been adapted via the transformation of multivariate Gaussian variables to model the topical distribution of documents in the presence of correlations among topics. In this paper, we propose a probit normal alternative approach to modelling correlated topical structures. Our use of the probit model in the context of topic discovery is novel, as many authors have so far concentrated solely of ...
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